Learning to Fuse Asymmetric Feature Maps in Siamese Trackers

This paper has been accepted by CVPR2021

paper: https://arxiv.org/abs/2012.02776

@article{han2020learning,
  title={Learning to Fuse Asymmetric Feature Maps in Siamese Trackers},
  author={Han, Wencheng and Dong, Xingping and Khan, Fahad Shahbaz and Shao, Ling and Shen, Jianbing},
  journal={arXiv preprint arXiv:2012.02776},
  year={2020}
}

weights and raw results

(Please remove the blank after https: by hand. It is used for anti-spider)

raw results https:// iiai-wencheng2.oss-cn-hongkong.aliyuncs.com/acm_raw_results.zip

config and weights for LaSOT https:// iiai-wencheng2.oss-cn-hongkong.aliyuncs.com/LaSOT_weight_config.zip

config weights for VOT https:// iiai-wencheng2.oss-cn-hongkong.aliyuncs.com/weight_VOT2019.zip

Installation

Please find installation instructions in INSTALL.md.

Quick Start: Using SiamBAN

Add SiamBAN to your PYTHONPATH

export PYTHONPATH=/path/to/siamban:$PYTHONPATH

Download models

Download models in Model Zoo and put the model.pth in the correct directory in experiments

Download testing datasets

Download datasets and put them into testing_dataset directory. Jsons of commonly used datasets can be downloaded from here or here, extraction code: 8fju. If you want to test tracker on new dataset, please refer to pysot-toolkit to setting testing_dataset.

Test tracker

cd experiments/siamban_r50_l234
python -u ../../tools/test.py 	\
	--snapshot model.pth 	\ # model path
	--dataset VOT2018 	\ # dataset name
	--config config.yaml	  # config file

The testing results will in the current directory(results/dataset/model_name/)

Eval tracker

assume still in experiments/siamban_r50_l234

python ../../tools/eval.py 	 \
	--tracker_path ./results \ # result path
	--dataset VOT2018        \ # dataset name
	--num 1 		 \ # number thread to eval
	--tracker_prefix 'model'   # tracker_name

License

This project is released under the Apache 2.0 license.

wencheng256/SiamBAN-ACM